Monitoring method, recommendation method and device for advertisement recommendation model

Abstract

The invention provides an advertisement recommendation model monitoring method and device, an advertisement recommendation method and device, electronic equipment and a computer readable storage medium. The method comprises the steps of for two adjacent model updating periods, obtaining a user sample which can be used when an advertisement recommendation model is trained in each model updating period to recommend an advertisement; determining a characteristic value quantile of a user characteristic type corresponding to the user sample; performing distribution estimation processing according to the eigenvalue quantiles to obtain eigenvalue probability distribution of the user feature types corresponding to each model updating period; measuring the difference between the characteristic value probability distributions of two adjacent model updating periods to obtain information divergence corresponding to the user characteristic type; and according to the information divergence, selecting a user sample from the user samples corresponding to the two adjacent model updating periods as a training sample. Through the method and the device, the sensitivity to characteristic value distribution fluctuation can be improved, the exception can be captured more accurately, and the advertisement recommendation precision is improved.

Description

technical field [0001] The present invention relates to artificial intelligence technology, in particular to a monitoring method for an advertisement recommendation model, a recommendation method, a device, electronic equipment and a computer-readable storage medium. Background technique [0002] Artificial Intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the nature of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. [0003] Advertisement recommendation is an important application direction of artificial intelligence. How to recommend advertisements that are mo...

AI Technical Summary

Problems solved by technology

Due to data timeliness considerations, features often undergo periodic updates, and some potential problems may occur during the update process, resulting in fluctuations in the distribution of feature values, which will ultimately affect the effect of advertising recommendations. Therefore, it is necessary to stabilize the features and advertising recommendation models. monitor

In the solutions provided by related technologies, feature monitoring is usually carried out through descriptive statistics, but the sensitivity of descriptive statistics to the fluctuation of feature value distribution is not high, and it cannot accurately reflect the abnormal distribution of feature values, which leads to the difficulty of advertising recommendation. poor accuracy

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